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A new Version of the Malusim Model on NEWA

The following is the message I received today from Dr. Terence Robinson, at Cornell University, regarding the 2019 version of the carbohydrate thinning model (aka; Malusim Model) on the NEWA website.

“We are pleased to announce the official release of the 2019 carbohydrate thinning model (Malusim) on the Newa website. The model will have an updated look and information. The input page will require growers to input the % of spurs that are flowering in one of 4 ranges (0-25, 26-50, 51-75 and 76-100%.). The output data table will have a column of DD base 4°C and will have colors highlighting when we are in the sweet spot for thinning (200-250DD from bloom). The new version will also give a Thinning Index composed of the average carb balance of 2 days before, the day of thinning and the next 4 days= 7 day running average. The thinning recommendations will be based on a new 3 dimensional lookup table taking into account, DD from bloom, % of spurs that are flowering and carb balance over 7 days. The thinning recommendation cells in the table will also be color coded to indicate red=high risk of overthinning, blue= mild thinning expected, yellow= caution possible aggressive thinning efficacy and green=good thinning efficacy.

We are pleased to announce the official release of the Malusim app, including an android and an iOS versions. You can download the app from the Google Play Store or the iTunes Store, OR use the app from any browser at https://malusim.org (note that speech recognition features are not supported in the browser version of the app).

IMPORTANT: If you used the 2018 beta version of the Malusim app for Android, you must uninstall it from your devices and download the new release from the Google Play Store. The data storage method has changed, and any changes you make to your data in the old app will not be accessible via the new app on any of the supported platforms.

You can continue to access any data that you entered last year – however, remember that when entering data for this year, you should clone any existing locations, rather than editing them and simply updating the year. Cloning will allow you to access data from previous years in the future”.